EPFL - Master in Financial Engineering

Pros:
-Technical courses where you learn all essential material to start a career in quant finance
-Cheap Tuition and great value: you get a good Uni name and good education for a fraction of the cost of similar programs
-similar living cost to London
-competitive profile within Switzerland if you are EU
-« some » London and Amsterdam firms and banks screen MFE students for interviews
-flexible program and you can extend studies to apply for more internships

Cons:
-Very few quant jobs in Switzerland and if you are non EU, you have 5-6 opportunities at best
-If you have 0 experience before the end of study internship it will be hard to get interviews
-EPFL Forum (career fair) opportunities are weak
-Career Service is very weak and provides very little guidance as students are expected to do no internships before the 6month end of study internship which is very impractical

Advice:
Do the program, fight to get a summer internship in London on your first year and prepare interviews on your own

The ETH program is somewhat similar with no internship requirements so would recommend EPFL MFE over ETH

Definitely a lot of work, not a lot of time to do side-projects if you want to have to a social life. Idk about admission for international students but if you did your bachelor at EPFL its ez to get in. About the courses, there is some math so thats good but I recommend taking electives where you program a lot since there a few courses where coding is important in the main branch. + Profs are great!

Pros:
1. Hardcore courses with strict standard. The courses include most of the Q-quant content, like derivatives, stochastic calculus, interest rate models etc. Those courses require students to have solid foundation of math. The exams are also hard and strict. Students need to spend quite a long time and understand it deeply to get a good result. It could be tough, but you could learn a lot if you want.
2. Low cost. The tuition is quite low compared with US universities.
3. Good Teaching Assistant. Most courses will have exercises. TAs are from Phd programs. In exercises, TA will describe the knowledge that was not clear in lecture and teach some important exercises in detail.
4. Compulsory internship. The program requires student to take 6-months internship and finish the master thesis in the final semester, which gives students at least one experience to take an internship in master study.
Cons:
1. Less internship chances. Switzerland does not have too much companies for quantitative finance compared with US and UK, which make it difficult for students to find an internship. For non-EU students, its more difficult as they need to apply work permit if they want to take an internship in other countries, like France, Germany, UK.
2. Career Service. The career service is not good. We can find internship chances in the portal. However, these chances are quite competitive, and most companies are not famous.
3. Hardcore courses. This could also be a disadvantage. It occupied too much time for students so they do not have much time to prepare for interviews. The courses are also traditional, which does not cover too much updated content, like ML, DL, AI, etc.
4. Alumni resources. We do not have too much alumni enter famous companies, like investment bank, hedge fund. For what I know, we only have two alumni successfully enter in famous hedge fund(DRW and Squarepoint) in 2025.

The master’s program is strong overall, providing solid knowledge across the most relevant topics in Financial Engineering. However, there are a few areas for improvement. I would suggest removing some mandatory courses to give students more flexibility to tailor their academic journey to their individual interests.

In general, the professors and TAs explain concepts clearly and often provide valuable insights and suggestions to help you explore topics in greater depth.

Finally, it would be very helpful to organize dedicated sessions to strengthen the specific skills required for quantitative interviews.

Very strong and diverse quantitative program. You can dive deep across many different fields within quant finance. Some exams and courses are quite tough but worth the hustle for such a competitive progam.

Expect technical courses that probe both math and code. Exams are tough and reward generalization: instead of repeating class problems, they push you to extend the theory to unfamiliar situations. Plus, a strong lineup of data-science classes lets you dive into cutting-edge machine-learning electives.